mlsanityData to 14 Oct 2026

Omni-Referring Image Segmentation

arXiv 2512.06862 ↗First posted 7 Dec 2025cs.CVcited by 2

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Abstract (arXiv)

In this paper, we propose a novel task termed Omni-Referring Image Segmentation (OmniRIS) towards highly generalized image segmentation. Compared with existing unimodally conditioned segmentation tasks, such as RIS and visual RIS, OmniRIS supports the input of text instructions and reference images with masks, boxes or scribbles as omni-prompts. This property makes it can well exploit the intrinsic merits of both text and visual modalities, i.e., granular attribute referring and uncommon object grounding, respectively. Besides, OmniRIS can also handle various segmentation settings, such as one v.s. many and many v.s. many, further facilitating its practical use. To promote the research of OmniRIS, we also rigorously design and construct a large dataset termed OmniRef, which consists of 186,939 omni-prompts for 30,956 images, and establish a comprehensive evaluation system. Moreover, a strong and general baseline termed OmniSegNet is also proposed to tackle the key challenges of OmniRIS, such as omni-prompt encoding. The extensive experiments not only validate the capability of OmniSegNet in following omni-modal instructions, but also show the superiority of OmniRIS for highly generalized image segmentation.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 48 of its 62 references that are in the map. First posted on arXiv 7 Dec 2025.

Builds on

48 of 62 references.

References · 48

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36 more
  1. 2023Segment Everything Everywhere All at Oncecited by 548
  2. 2018MAttNet: Modular Attention Network for Referring Expression Comprehensioncited by 431
  3. 2021CRIS: CLIP-Driven Referring Image Segmentationcited by 353
  4. 2021LAVT: Language-Aware Vision Transformer for Referring Image Segmentationcited by 348
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  8. 2023GRES: Generalized Referring Expression Segmentationcited by 254
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  10. 2021Vision-Language Transformer and Query Generation for Referring Segmentationcited by 240
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  12. 2020Multi-task Collaborative Network for Joint Referring Expression Comprehension and Segmentationcited by 204
  13. 2023GSVA: Generalized Segmentation via Multimodal Large Language Modelscited by 154
  14. 2023PolyFormer: Referring Image Segmentation as Sequential Polygon Generationcited by 148
  15. 2023Matcher: Segment Anything with One Shot Using All-Purpose Feature Matchingcited by 142
  16. 2022SeqTR: A Simple yet Universal Network for Visual Groundingcited by 139
  17. 2022Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentationcited by 114
  18. 2024T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergycited by 94
  19. 2023Hierarchical Dense Correlation Distillation for Few-Shot Segmentationcited by 84
  20. 2024VRP-SAM: SAM with Visual Reference Promptcited by 75
  21. 2023Beyond One-to-One: Rethinking the Referring Image Segmentationcited by 68
  22. 2022Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentationcited by 65
  23. 2023Visual In-Context Promptingcited by 52
  24. 2024Toward Visual Grounding: A Surveycited by 52
  25. 2024ReMamber: Referring Image Segmentation with Mamba Twistercited by 38
  26. 2024SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusioncited by 36
  27. 2024Bridge the Points: Graph-based Few-shot Segment Anything Semanticallycited by 35
  28. 2023Unveiling Parts Beyond Objects:Towards Finer-Granularity Referring Expression Segmentationcited by 22
  29. 2024Visual Prompting for Generalized Few-shot Segmentation: A Multi-scale Approachcited by 15
  30. 2025Hybrid Global-Local Representation with Augmented Spatial Guidance for Zero-Shot Referring Image Segmentationcited by 14
  31. 2024Visual Prompt Selection for In-Context Learning Segmentationcited by 13
  32. 2025Unlocking the Power of SAM 2 for Few-Shot Segmentationcited by 11
  33. 2024CoHD: A Counting-Aware Hierarchical Decoding Framework for Generalized Referring Expression Segmentationcited by 10
  34. 2025WeakMCN: Multi-task Collaborative Network for Weakly Supervised Referring Expression Comprehension and Segmentationcited by 9
  35. 2025Latent Expression Generation for Referring Image Segmentation and Groundingcited by 6
  36. 2024Deep Instruction Tuning for Segment Anything Modelcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Mixture-of-Thought-Tokens: Unifying Perception and Reasoning for Free-form Multimodal Groundingcited by 1
  2. 2026UniEvo-RS: Omni-Prompt Unified Remote Sensing Segmentation with Representative Exemplar-Driven Prototype Evolutioncited by 0